The text compares two models introduced by OpenAI, o3-mini and o3, designed to enhance software verification capabilities. The author created a dataset of 210 programs with subtle bugs across multiple programming languages, including Python, TypeScript, Go, Rust, and Ruby. Both models exhibited strong overall performance, with only a slight advantage for the larger o3 model in certain situations. Performance analysis by language revealed equal or slightly better results for o3-mini in some languages, but stronger and more consistent performance in others like Rust. The author suggests that the smaller-scale o3-mini incorporates effective reasoning capabilities comparable to the larger o3 model, while the slight edge of OpenAI o3 may provide benefits in handling nuanced logical and semantic issues, particularly in Ruby.